Interested in this AI Engineering Manager role at adMarketplace?
Apply Now →Skills & Technologies
About This Role
Who We Are
At adMarketplace, our mission is to deliver the most engaging consumer search experiences while empowering advertisers to measure media performance accurately. Today, millions of people worldwide engage with our exclusive, transparent media placements across the internet's leading browsers, shopping apps, and review sites.
Our award-winning culture is built around five core values (known as our 5C's): Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness. With these guiding values, adMarketplace seeks to empower our team to reach their full potential through continued learning, and the opportunity to do their best work.
The Role
We are seeking an accomplished AI/ML leader with a proven track record of building and scaling high-performing machine learning teams. As a Manager in our established AI/ML and Search organization, you will play a pivotal role in shaping our machine learning strategy, guiding the development and deployment of innovative models that drive significant improvements in our ad serving platform and consumer-facing search products. This is a hands-on leadership position that requires both deep technical expertise and exceptional people management skills.
Responsibilities
- Define and execute a comprehensive machine learning strategy aligned with our overall business goals. Stay ahead of industry trends and identify opportunities to leverage emerging technologies to gain a competitive advantage.
- Recruit, develop, and retain top machine learning talent. Promote a collaborative and inclusive environment that encourages innovation and experimentation. Provide technical guidance and mentorship to team members, empowering them to reach their full potential.
- Oversee a portfolio of machine learning projects, ensuring alignment with strategic priorities, effective resource allocation, and timely delivery of high-quality solutions.
- Build strong partnerships with product management, engineering, data science, and other stakeholders to ensure seamless integration of AI/ML models into existing systems and workflows. Advocate for the value of machine learning across the organization.
- Set clear performance expectations, provide regular feedback, and conduct performance reviews for team members. Identify and address performance gaps to ensure continued growth and development of the team.
- Maintain a deep understanding of the technical landscape and ensure the team is using the latest tools, techniques, and best practices in machine learning. Actively participate in architecting solutions, providing hands-on technical guidance, and contributing code when necessary (30-40% of the time).
- Lead by example in code quality and establish rigorous code review processes to ensure high standards of maintainability, scalability, and performance. Mentor team members on best practices and promote a culture of continuous improvement.
- Represent the team in internal and external forums, sharing insights and best practices in machine learning. Contribute to the broader AI/ML community through publications, presentations, or open-source contributions.
Basic Qualifications
- A PhD or MS in a quantitative field (e.g., Computer Science, Statistics, Mathematics) with 10+ years of experience in AI/ML, including 5+ years of demonstrated success leading and managing technical teams in a fast-paced environment.
- Proven ability to build and lead high-performing teams, inspire innovation, and drive results. Strong communication and interpersonal skills, with the ability to influence and build consensus across diverse stakeholders.
- Deep understanding of machine learning algorithms, statistical modeling, and data analysis techniques. Experience with a wide range of ML tools and frameworks, as well as cloud-based infrastructure.
- Demonstrated expertise in building and deploying ML models in one or more relevant domains, such as ads, relevance, ranking, recommendation systems, or search.
- Understanding of the business implications of AI/ML technologies and the ability to translate technical solutions into tangible business value.
- Proven ability to write production-level code and architect complex AI/ML systems.
Preferred Qualifications
- Track record of presenting at industry conferences, publishing research papers, or contributing to open-source AI/ML projects.
- Experience starting or leading new AI/ML initiatives within an organization, demonstrating the ability to identify and capitalize on opportunities.
- Passion for developing and mentoring others, with a track record of helping individuals grow their technical and leadership skills.
- Compensation Range: $250,000 - $275,000 + Bonus & Equity
#LI-Onsite
Join Us
adMarketplace has been named as one of the best places to work in New York City by Built In and Crain's- the latter of which have recognized us the past three years straight! AMP is currently experiencing triple digit growth, and it's never been a better time to join our team!
We offer a robust continuing education program, management training, regular company-wide lunch and learns, and well-defined career paths to ensure all our employees have an opportunity to grow.
At adMarketplace, we play to win, but we learn from our setbacks. Our commitment to a collaborative environment means no one succeeds alone, and no one fails alone either.
We know you've come to expect comprehensive healthcare, wellness programs, paid time off, commuter benefits, and 401k matching from any company, so it's a good thing we offer all of that and so much more. adMarketplace offers Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and corporate retreats to encourage a strong work/life balance.
No Third Party Recruiters. We do not accept unsolicited agency resumes and we are not responsible for any fees related to unsolicited resumes.
- This range represents the low and high end of the base salary someone in this role may earn as an employee of adMarketplace in the New York office. Salaries will vary based on various factors including but not limited to professional and academic experience; training; associated responsibilities; and other business and organizational needs. The range listed is just one component of our total compensation package for employees. Salary decisions are dependent on the circumstances of each hire.
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 37,339 AI roles we're tracking, AI Engineering Manager positions make up 0% of the market. At adMarketplace, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Engineering Manager roles pay a median of $293,500 based on 21 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $225,000. This role's midpoint ($262K) sits 11% below the category median. Disclosed range: $250K to $275K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Safety ($274,200) and Research Engineer ($260,000). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
adMarketplace AI Hiring
adMarketplace has 1 open AI role right now. They're hiring across AI Engineering Manager. Based in New York, NY, US. Compensation range: $275K - $275K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national median.
Career Path
Common paths into AI Engineering Manager roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (3,672) are outnumbered by mid-level (23,272) and senior (7,048) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.